We use another approach to improve the efficiency of exploration and speed up convergence. Variational information maximizing exploration (VIME) [1]} provides an effective framework for exploring an unknown environment of RL. VIME proposes a curiosity-driven exploration strategy. In the dynamic model, it takes the information gain obtained from the agent's internal belief as a driving force. The characteristic of this exploration algorithm is that the information owned by the agent is regarded as part of the state, and the agent hopes to obtain new information by traversing new states.
